Consecutive corrupted MBs or slice errors are commonly seen in modern video transmission systems. Temporal error concealment is an effective approach to reduce the impact of errors. Conventional temporal error concealment techniques recover slice errors on a MB basis. We propose a new novel temporal scheme for slice error concealment based on a size-adaptive region basis. Size-adaptive region boundary matching can significantly reduce the misalignments or side mismatches that are commonly seen in MB-based approaches. Instead of using MSE or MAE as the matching criteria, We propose a matching criterion based on structural similarity (SSIM). Our proposed matching criterion can achieve better structural alignments and better visual perceptual quality. We also propose a method to detect motion vector outliers at the last stage of the error concealment scheme, which can further improve the visual quality of the concealed videos. Our proposed scheme conceals slice errors with good accuracy as well as low computation complexity, and it can be applied for real-time applications.

Video transmission over wireless networks suffers from packet loss due to either temporary packet drop or fading-induced bit errors. To ensure that the quality of the decoded video is not overly affected by the channel unreliability, the video applications have to provide sufficient robustness. In this paper, a novel slice interleaving algorithm is proposed for compressed video packetization. Each packet is constructed by interleaving independently decodable slices of the coded video bit-stream in a group of frames. We group slices into packets according to the maximum minimal distance of these slices. The scattered pattern guarantees that each lost slice has, as many as possible, spatial and temporal neighbors that belong to other correctly received packets. This scheme greatly strengthens the error concealment performance compared with traditional methods. Experimental results demonstrate the superiority of the proposed algorithm.

Video communication is often afflicted by packet loss over unreliable networks. To alleviate the quality degradation in the situation of packet loss, this paper proposes a novel error resilient slice interleaving method for compressed video packetization. Each packet is constructed by interleaving independently decodable slices of the coded video bit-stream in consecutive frames. The optimal interleaving pattern for minimizing the overall distortion of the decoded video, subject to a delay constraint, is determined based on the error concealment technique employed at the user end. Compared with traditional error-resilient methods, this scheme greatly improves the overall performance without requiring an increase in bit-rate. Experimental results on different video sequences demonstrate the effectiveness of the proposed approach.

The paper describes a fast MPEG-2 to H.264 transcoder by leveraging the MPEG-2 metadata set to reduce the computational complexity of the H.264 encoding process. With the proposed fast transcoding algorithms, our software-based transcoder can perform real-time transcoding a MPEG-2 movie from a DVD disc (at D1 resolution and full frame-rate) and simultaneously performing RTP/UDP streaming of the H.264 video with AC-3 audio over IP networks using only a 1.6 GHz PC notebook. We can achieve about 20-30% faster than the full re-encoding method even at the same target bit-rate and without visible quality degradation. Benchmarking with existing software systems has shown similar results.

Due to the advance of technologies in multimedia compression and network communications, scalable media streaming services have been availed to provide QoS differentiated services for heterogeneous users. However, it is still a big challenge to support consistent end-to-end Quality of Services (QoS) for the users due to the dynamic feature of the Internet, and abrupt variability of the network resources may severally affect the client perceived QoS. In this paper, we address the issues of smooth QoS adaptation for scalable streaming services. We propose an Optimal Smooth QoS Adaptation (OS-QA) strategy which allocates the server resource adaptively to cope with the variability of network bandwidth and protects the service quality of different quality classes under dynamic resource constraints. We analyze the quality variation caused by resource fluctuation and proposed OS-QA to minimize the average QoS variance under the resource constraints. Simulations are conducted to compare our proposed method with other QoS adaptation methods, and performance is analyzed in terms of QoS variance and PSNR. Results show that our proposed method is able to gracefully adapt the QoS and protect the client perceived QoS by minimizing the QoS variance under dynamic network resource constrains.

Temporal scalability in H.264/SVC video compression standard can be achieved with the hierarchical B-pictures (HB) structure. When performing motion estimation (ME) in the HB structure, the temporal distance between the current frame and reference frame(s) can be large (up to 32 frames apart). This limits the performance of fast search algorithm as larger search window is often necessary. Extensive experiments showed that popular fast suboptimal block ME algorithms are ineffective at tracking large motions across several frames. In this paper, we propose a new framework called Lacing which integrates well with any fast block ME techniques to significantly improve the motion prediction accuracy in quality of the motion-compensated frame and also result in smoother motion vector fields with lower entropy.